It is often difficult for autonomous cleaning robots to ensure full (e.g., above a specified amount, like 95% or 99%) coverage of a workspace, particularly given time, compute, and power constraints imposed by many commercial use cases. Several efforts have been made to address this challenge. During operation, some traditional surface coverage robotic devices cover (e.g., apply some cleaning treatment, like vacuuming or mopping to) the surface of a workspace by moving over the workspace randomly or some devices follow a particular surface coverage pattern. With random surface coverage, the robotic device will likely reach all areas of the workspace, so long as it is operated long enough. However, such approaches are often inefficient and result in uneven cleaning. Furthermore, overlapping of serviced areas is likely to occur with random coverage.
Robotic cleaning devices may also follow a systematic surface coverage pattern. With systematic surface coverage, the robotic device follows a predetermined (e.g., hand-coded without contextual logic) pattern of movement, such as crossing the floor in parallel rows. This approach often provides an even and controlled surface coverage method for the robotic device. However, since systematic paths are predetermined, the structure of the pattern may not be able to adapt to different workspaces and may therefore be too rigid to cover all areas of the workspace without, for example, repeat coverage of areas or increased coverage time.
Additional attempts to improve surface coverage efficiency may involve complex mapping systems requiring expensive technology, including additional sensors, image processors, advanced processors, GPS etc. for monitoring covered surfaces of the workspace to, for example, ensure all areas are reached by the robotic device in a timely manner and avoid repeat coverage of areas. In those instances, acquisition and maintenance costs may be prohibitive. A need exists for a more economical and practical solution to reduce or eliminate surface coverage redundancy and improve surface coverage efficiency of a workspace. As such, methods and systems for surface coverage of a workspace by a robotic device are presented herein. None of the preceding should be read as a disclaimer of subject matter, which is not to suggest than any other discussion of design tradeoffs herein is such a disclaimer.